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The A-Train Cloud Segmentation Dataset

Metadata Updated: July 10, 2025

ATCS is a dataset designed to train deep learning models to volumetrically segment clouds from multi-angle satellite imagery. The dataset consists of spatiotemporally aligned patches of multi-angle polarimetry from the POLDER sensor aboard the PARASOL mission and vertical cloud profiles from the 2B-CLDCLASS product using the cloud profiling radar (CPR) aboard CloudSat.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources

Dates

Metadata Created Date April 11, 2025
Metadata Updated Date July 10, 2025

Metadata Source

Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date April 11, 2025
Metadata Updated Date July 10, 2025
Publisher NASA/GSFC/SED/ESD/GCDC/OB.DAAC;NASA/GSFC/SED/ESD/GCDC/SeaBASS
Maintainer
Identifier 10.5067/SeaBASS/ATCS/DATA001
Data Last Modified 2025-07-09
Category Earth Science
Public Access Level public
Bureau Code 026:00
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id 275ad6fc-a87c-44a8-9851-686d97212265
Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
Harvest Source Title NASA Data.json
Old Spatial {"EastBoundingCoordinate":180.0,"NorthBoundingCoordinate":90.0,"SouthBoundingCoordinate":-90.0,"WestBoundingCoordinate":-180.0},"CARTESIAN"
Program Code 026:000
Source Datajson Identifier True
Source Hash c90c9ec75162621c760c8d252ecdebbfb1a0b85ae3bfe754cac1d085e18c9160
Source Schema Version 1.1
Spatial

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